Closely connected to the concept of information cascades is the self-organizing system. Such a system will organize itself without any centralized hierarchal structure, but rather through many automatic decentralized processes.

One particularly striking, if morbid, example of a self-organizing system is an ant mill: first described by naturalist William Beebe, an ant mill occurs when a large number of drones are separated from the colony. Unable to find their way back, the drones walked in a large circle (1200 feet in circumference) for days, until they all keeled over dead. They were all obeying a simple rule while lost – follow the ant in front of you.

These ant mills are actually fairly common, and are often stopped by a single ant or small group of ants straying from the course accidentally, thus inadvertently saving their entire colony. An ant mill is a clear example of an information cascade, both as ants enter and leave the mill, and of a self-organizing system.

Another example is certain species of firefly, which will perfectly synchronize their lights within a certain degree of locality. Again, this happens without any centralized organizational structure, and may be due to a process very much like the one we’ve been discussing in class, although it’s not fully understood how the bugs synchronize.

In a paper written by Thomas D. Seeley at our very own Cornell University’s department of Neurobiology, he defines a system as self-organized whenever it contains a large number of subunits which lack the wherewithal to implement centralized control. Note that this perfectly describes a college student body, in which many examples of information cascading may be seen vis a vis fashion, course choices, and so forth. However, a student body doesn’t really achieve any communal goal, so it’s hard to classify it as a self organizing system. Maybe if we weren’t so lazy.

Thomas Seeley paper: http://www.biolbull.org/cgi/reprint/202/3/314.pdf